With advancement in technology, especially imaging field, digital image forgery has increased a lot nowadays. In order to counter this problem, many detection techniques have been developed from time time. For rapid and accurate of forged image, novel hybrid technique is used research work that implements Gray Level Co-occurrence Matrix (GLCM) along with Binary Robust Invariant Scalable Keypoin...

This paper presents preliminary results for the classiication of Pap Smear cell nuclei, using Gray Level Co-occurrence Matrix (GLCM) textural features. We outline a method of nuclear segment-ation using fast morphological gray-scale transforms. For each segmented nucleus, features derived from a modiied form of the GLCM are extracted over several angle and distance measures. Linear Discriminant...

Texture classification is an active topic in image processing which plays an important role in many applications such as image retrieval, inspection systems, face recognition, medical image processing, etc. There are many approaches extracting texture features in gray-level images such as local binary patterns, gray level co-occurence matrixes, statistical features, skeleton, scale invariant fe...

In this paper we describe a super-resolving approach based upon gray level coding of the information. Thus, the imaged object should have limited number of gray levels. The proposed approach overcomes the resolution limitations caused either by the optics or by the finite size of the detector. In contrast to other existing super resolution techniques that use time or wavelength multiplexing, in...

Ultrasound applications are used for diagnostic applications such as visualizing muscles, tendons, internal organs, to determine its size, structures, any lesions or other abnormalities. This paper concentrates the diagnosis of abnormalities in kidney Images based on retrieving past similar images from kidney Image Database. More and more amount of ultrasound digital images are being captured a...